检索结果-内蒙古大学图书馆

10th Annual ieee Symposium on computational intelligence in bioinformatics and computational biology (CIBCB)

作者： Reddy, U. Srinivasulu Arock, Michael Reddy, A. V. Natl Inst Technol Dept Comp Applicat Tiruchirappalli Tamil Nadu India

ISBN: (纸本)9781467358750

In bioinformatics, Planted (l, d)-Motif finding is an important and challenging problem, which has many applications. Generally, it is to locate recurring patterns in the promoter regions of co-expressed or co-regulated genes. As we can't expect the pattern to be exact matching copies owing to biological mutations, the motif finding turns to be an NP-complete problem. By approximating the same in different aspects, scientists have provided many solutions in the literature. These solutions are either "exact" or "approximate". All the proposed exact solutions take exponential-time;they need more time to search for larger parameters l and d. The problems of bioinformatics seldom need the exact optimum solution;rather what they need is robust, fast and near optimal solutions. Therefore, it is impractical to use an exact algorithm to search for large parameters of motifs in real biological dataset. In this paper, we have adopted the features of the Particle Swarm Optimization (PSO) with k-nearest neighbor algorithm to solve the Planted (l, d)-Motif Finding Problem. PSO is a global approximation optimization technique and has wide applications. It finds the global best solution by simply adjusting the trajectory of each individual towards its own best location and towards the best particle of the swarm at each generation. We have performed some experiments on synthetic data by increasing number of sequences and the length of the sequences for different (l, d)-Motifs for the following data sets: general instances (10, 2), (11, 2), (12, 3), (15, 4), (16, 5), (18, 6), (20, 7) (30, 11) and (40,15). Challenging instances: (9, 2), (11, 3), (13, 4), (15, 5), (20, 7), (30, 11), (40, 15) and finally, we have applied our proposed method for real biological sequences. From the experimental results we observe that the proposed algorithm is more efficient and accurate compared to existing approximation algorithms and even it works better for larger motif instances.

关键词： Motif Finding Particle Swarm Optimization (PSO) Swarm intelligence (SI) Transcriptional Factor Binding Sites (TFBS) Gene regulation Planted (l, d)-Motifs K-Nearest-Neighbor Algorithm (KNN)

来源：评论

学校读者我要写书评

暂无评论

Genomic Machine Learning Meta-regression: Insights on Associations of Study Features With Reported Model Performance

引用

ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2024年第1期21卷 169-177页

作者： Barnett, Eric J. Onete, Daniel G. Salekin, Asif Faraone, Stephen V. SUNY Upstate Med Univ Dept Psychiat & Behav Sci Syracuse NY 13210 USA SUNY Upstate Med Univ Coll Med MD Program Syracuse NY 13210 USA Syracuse Univ Dept Elect Engn & Comp Sci Lab Ubiquitous & Intelligent Sensing Syracuse NY 13210 USA

Many studies have been conducted with the goal of correctly predicting diagnostic status of a disorder using the combination of genomic data and machine learning. It is often hard to judge which components of a study led to better results and whether better reported results represent a true improvement or an uncorrected bias inflating performance. We extracted information about the methods used and other differentiating features in genomic machine learning models. We used these features in linear regressions predicting model performance. We tested for univariate and multivariate associations as well as interactions between features. Of the models reviewed, 46% used feature selection methods that can lead to data leakage. Across our models, the number of hyperparameter optimizations reported, data leakage due to feature selection, model type, and modeling an autoimmune disorder were significantly associated with an increase in reported model performance. We found a significant, negative interaction between data leakage and training size. Our results suggest that methods susceptible to data leakage are prevalent among genomic machine learning research, resulting in inflated reported performance. Best practice guidelines that promote the avoidance and recognition of data leakage may help the field avoid biased results.

关键词： Data models Predictive models Training Genomics bioinformatics Machine learning computational modeling learning artificial intelligence computing methodologies biology and genetics life and medical sciences computer applications

来源：评论

学校读者我要写书评

暂无评论

computational intelligence in surgery and diagnosis

Computational intelligence in surgery and diagnosis

引用

20th Annual International conference of the ieee-Engineering-in-Medicine-and-biology-Society

作者： Micheli-Tzanakou, E Rutgers State Univ Dept Biomed Engn Piscataway NJ 08854 USA

ISBN: (纸本)0780351649

We have used advanced signal processing and innovative image processing methods that are used outside the operating room. The software is written in C++ in a windows environment and can be used on any PC. We will demonstrate some applications on a laptop. Applications to be long with computational intelligence for diagnostic purposes and as visualization aids inside and demonstrated, include blood cell classification, mammography, evoked potentials, ophthalmology, EEG and field potentials in Parkinson's disease. The latter methods along with 3D reconstruction of MRI images of Parkinsonian patients, are currently used in the operating room for Pallidotomies.

关键词： Computer aided diagnosis

来源：评论

学校读者我要写书评

暂无评论

Remote Pulse Rate Variability Measurement with Adaptive Slope Sum Function 11

Remote Pulse Rate Variability Measurement with Adaptive Slop...

引用

11th International conference on bioinformatics and computational biology (ICBCB)

作者： Kehang Yang Peixi Li Zhejiang Gongshang Univ Sussex Artificial Intelligence Inst Hangzhou Peoples R China

ISBN: (纸本)9798350397871

Compared to Electrocardiography (ECG) and contact Photoplethysmography (PPG), the signal obtained from remote Photoplethysmography (rPPG) is much more noisy due to the body movement, light variation, sensor noise, low scanning frequency of the cameras, etc. As a result, the measurement of Pulse Rate Variability (PRV) based on rPPG is a more challenging task than measuring PRV and Heart Rate Variability (HRV) from contact PPG and ECG, because it requires precise peak detection on the noisy rPPG signal. To address this issue, some researchers used slope sum function (SSF) to enhance the rising trend of the signal and reduce the downward trend of it, so that the signal became more clear and easier for peak detection. This method is relatively effective, but it has some disadvantages. Firstly, the window size of the SSF is set manually. Secondly, there is a shift between the peaks on the new signal generated by the SSF and the original signal. Thirdly, the parameter is fixed for the entire dataset, which is not ideal for real-life scenario where there are sudden changes in signal. In this paper, we proposed a novel algorithm which adaptively and automatically set the window size of SSF using continuous wavelet transform. We experimentally showed that the proposed method improved the remote measurement of PRV compared to the existing methods in the rPPG framework. We believe that our contribution is conducive to practicalization and commercialization of the related research.

关键词： Remote Photoplethysmography Peak Detection Pulse Rate Variability Slope Sum Function Continuous Wavelet Transform

来源：评论

学校读者我要写书评

暂无评论

Branching Out to Speciation in a Model of Fractionation: The Malvaceae

引用

ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2021年第5期18卷 1875-1884页

作者： Zhang, Yue Zheng, Chunfang Islam, Sindeed Kim, Yong-Min Sankoff, David Univ Ottawa Dept Math & Stat Ottawa ON K1S 2C3 Canada Korea Res Inst Biosci & Biotechnol Korean Bioinformat Ctr Daejeon 34141 South Korea

Fractionation is the genome-wide process of losing one gene per duplicate pair following whole genome doubling (WGD). An important type of evidence for duplicate gene loss is the frequency distribution of similarities between paralogous gene pairs in a genome or orthologous gene pairs in two species. We extend a previous branching process model for fractionation, originally accounting for paralog similarities, to encompass the distribution of ortholog similarities, after multiple rounds of whole genome doubling and fractionation, with the speciation event occurring at any point. We estimate the fractionation rates during all the inter-event periods in each lineage of the plant family Malvaceae. We suggest a major correction of the phylogenetic position of the durian sub-family, and discover a new triplication event in this lineage.

关键词： bioinformatics Genomics Fractionation Phylogeny Trajectory Biological system modeling computational modeling Whole genome duplication fractionation branching process gene pair similarity distribution Malvaceae durian

来源：评论

学校读者我要写书评

暂无评论

Modeling and Simulation Studies of Complex Biological Systems for Precision Medicine and Healthcare

引用

ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2019年第1期16卷 91-92页

作者： Shen, Bairong Jiang, Xiaoqian Zhao, Xing-Ming Soochow Univ Ctr Syst Biol Suzhou 215006 Peoples R China UTHealth Sch Biomed Informat Houston TX 77030 USA Fudan Univ Inst Sci & Technol Brain Inspired Intelligence Shanghai 200433 Peoples R China

Here present three articles on the private preservation of genome or electronic health record (EHR) data. Three articles focus on the algorithm developing for the analysis of GWAS and EHR-based phenotyping as well as electrocardiogram (ECG)-based disease recognition and classification. Here also include an article developing an algorithm for repositioning of old drugs for their new applications. The articles in this special section proposed several computational model and simulation methods to address diverse medical and healthcare issues which will be helpful to the promotion of the cross-disciplinary researches on the translational medicine and healthcare.

关键词： Diseases Drugs Electrocardiography Electronic Health Records Genomics Health Care Medical Signal Processing Signal Classification Drugs EHR Based Phenotyping Data Translational Medicine computational Model Electrocardiogram Based Disease Classification Electrocardiogram Based Disease Recognition GWAS Electronic Health Record Data Genome Healthcare Complex Biological Systems Special Issues And Sections Biological System Modeling Diseases Data Models Data Privacy Big Data Precision Engineering Medical Services Genomics

来源：评论

学校读者我要写书评

暂无评论

Editorial: Special Section on Bio-Inspired Swarm Computing and Engineering

引用

ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2017年第1期14卷 1-3页

作者： Tan, Ying Shi, Yuhui Peking Univ Sch Elect Engn & Comp Sci Dept Intelligence Sci Beijing 100873 Peoples R China Xian Jiaotong Liverpool Univ Dept Elect & Elect Engn Suzhou 215123 Peoples R China

Presents the introductory editorial for this issue of the publication.

关键词： Special issues and sections Particle swarm optimization Ant colony optimization Clustering methods Feature extraction Path planning Biological systems

来源：评论

学校读者我要写书评

暂无评论

Mobile access to on-line analytic bioinformatics tools 3

Mobile access to on-line analytic bioinformatics tools

引用

3rd International Work-conference on bioinformatics and Biomedical Engineering, IWBBIO 2015

作者： Del Pino, Sergio Díaz Karlsson, Tor Johan Mikael Cano, Juan Falgueras Trelles, Oswaldo Computer Architecture Department Málaga University Louis Pasteur 35 Málaga 29071 Spain Integromics S.L Parque Tecnológico de Ciencias de la Salud Avenida de la Innovación nº 1 Armilla Granada 18100 Spain Computer Sciences Department Malaga University Louis Pasteur 35 Malaga 29071 Spain Spain

ISBN: (纸本)9783319164793

The use of mobile devices grow continuously in many aspects of our everyday lives. It is essential that bioinformatics and biomedicine adapt to this trend because these platforms can provide universal access to computational resources independently of their location. We report the implementation of a light-weight client which allows researchers to launch complex analysis experiments and monitor the progress using their mobile devices. Starting from the analysis of existing functionality in current bioinformatics clients for webservices, we have selected, designed and implemented a complete set of functions for accessing computational resources in bioinformatics and biomedicine through mobile devices. © Springer International Publishing Switzerland 2015.

关键词： Web services

来源：评论

学校读者我要写书评

暂无评论

Analysis of Interacting Factors Contributing to the Onset of Diabetes Type 2 in the Female Pima Population: A Step towards Understanding the Links

Analysis of Interacting Factors Contributing to the Onset of...

引用

ieee conference on computational intelligence in bioinformatics and computational biology (CIBCB)

作者： Dobromyslin, Vitaly, I Megherbi, Dalila B. Univ Massachusetts Ctr Comp Machine Human Intelligence Networking & Lowell MA 01854 USA Instrumentat Lab Acute Care Analyt Dept Bedford MA 01730 USA

ISBN: (纸本)9781728194684

One of the biggest challenges in building predictive models relates to proper feature selection. As it is well known, good feature selection will result in accurate prediction independently of the classifier. We propose a novel processing pipeline consisting of unsupervised clustering to balance the class prevalence in the training set, which enables the development of stable models with less overfitting. In this paper, we use the proposed pipeline to predict the onset of Type 2 Diabetes (T2D) in the female Pima American Indian population. The Pima population, living near Phoenix, Arizona in the United States, has been known to have the highest T2D prevalence. While it generally remains unclear how various physiological variables and interacting risk factors contribute to the onset of T2D, here for the first time, we quantify the contribution of each of the physiological variables and their interactions to the predicted probability of developing T2D. Our findings in the adult Pima female T2D cohort point to the existence of two distinct population sub-groups, separated primarily by age and the number of pregnancies. For the first time in this dataset, we show several factor interactions: a) subjects with lower BMI (26.0 +/- 2.2 vs. 41.5 +/- 4.9) experienced a 57-78% reduction in T2D conversion rate at the high plasma glucose (>133.7 mg/dL) and high serum insulin (>168.0 pmol/L) levels respectively, and b) low serum insulin (70.1 +/- 16.7 vs. 294.7 +/- 136.6 pmol/L) was associated with a 90% lower risk of T2D conversion rate in individuals with high triceps skin thickness (>34 mm), and interestingly c) non-hypotensive (85.6 +/- 7.2 vs. 54.3 +/- 7.7 mm Hg) women with <= 1 pregnancy had 81% lower risk of T2D conversion. With an increasing number of pregnancies, the trend reversed, and non-hypotensive women experienced a 41% higher rate of T2D conversion. Through the evaluation of multiple feature selection methods and classifiers, we show the potential value of the pro

关键词： Type 2 Diabetes unsupervised machine learning clustering factor interaction analysis Pima American Indians diabetes population cardiovascular predictors for post-pregnancy chronic disease development in the Pima population

来源：评论

学校读者我要写书评

暂无评论

Comparative finite element analysis of patient-specific tricuspid and bicuspid aortic valve 17

Comparative finite element analysis of patient-specific tric...

引用

17th ieee International conference on bioinformatics and Bioengineering (BIBE)

作者： Djorovic, Smiljana Filipovic, Nenad Milosavljevic, Aleksandar Velicki, Lazar Univ Kragujevac Fac Engn Kragujevac Serbia Res & Dev Ctr Bioengn BioIRC Kragujevac Serbia Inst Cardiovasc Dis Sremska Kamenica Serbia

ISBN: (纸本)9781538613245

The main purpose of this study was to examine and compare the biomechanical characteristics of a healthy tricuspid aortic valve (TAV) and diseased bicuspid aortic valve (BAV). The patient-specific geometrical model of TAV was created based on computed tomography (CT) scan images. On the same model, two leaflets (left and right) were manually fused in order to create the BAV model (type 1). The finite element analysis was performed using the algorithms and numerical methods for structural analysis on computational meshes. Also, equivalent material characteristics and boundary conditions were applied. As the result, displacements and Von Mises stress distribution were computed concerning anatomical differences between TAV and BAV structures. In the case of TAV, leaflets were symmetrically and centrally open, while BAV analysis resulted with regions of increased stresses on the leaflets with elliptically open valve. The performed comparative computational analysis gave better insight into the biomechanics of healthy and malformed aortic root. It may contribute to monitoring of structural characteristics due to the difficulty of obtaining such characteristics in vitro or in vivo.

关键词： tricuspid aortic valve bicuspid aortic valve computational analysis finite element method

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：